Demand Intelligence Architecture

Which comes first? The right BI solution or the right BI architecture?

Hands down, it’s the right business intelligence (BI) architecture. If your enterprise currently uses retail demand data in a manner that favors either tier one (corporate users) or tier two members (retail sales team) — then you don’t have the right architecture in place. And that means you don’t have the right demand intelligence (DI) solution.

Early entrants into the BI market developed software solutions that either favored top-down or bottom-up decision-making — solutions that suit Outside-In or Inside-Out BI architectures. That just doesn’t cut it in today’s highly competitive global market. Today, retailers have higher on-shelf, in-store and across-the-chain expectations. They want their customers to get the goods they want, when and where they want them, and they can’t afford to be exposed to high-risk inventory overstocks and out-of-stocks.

To meet retailer expectations and grow volume, you need an Outside-Inside-Throughout BI architecture in place first, one that seamlessly integrates internal and POS demand dataacross your enterprise — across all teams and tiers — and encourages swift insight and decision-making by every member of the executive and retail teams. Then you need to choose a complementary BI solution that consistently funnels timely, unified internal and demand data to exactly the right person — whatever their position in the enterprise — based on that person’s needs.

BI architecture strategy is at the core of getting the right strategic demand side BI solution installed. Whether you’re an early-adopter with a dated BI solution that doesn’t meet yourneeds or you still haven’t taken the BI plunge, understand this — there’s still time to get it right. This white paper can serve as a resource for companies both new to and experienced with BI. It outlines the benefits and limits of three BI architectures — one of which is ideal — and provides your enterprise with the key steps to choosing and implementing a custom-fit BI solution.